How to evaluate Data Science models ?

Lift Charts & Gain Charts: These are widely used in campaign targeting problems, to determine which decile can we target customers for a specific campaign. Also, it tells you how much response you can expect from the new target base. ROC Curve: The ROC curve is the plot between false positive rate and True Positive rate. Gini coefficient: This is the ratio of area between the ROC curve and the diagonal line & the area of the above triangle Cross Validation: splitting the data into two parts, where one part is used for "training" your model, and the second part is used to make predictions. By this you can test the model on the data that was "not seen" by it previously, and check how it could possibly behave with external data.